Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 239.13 +/- 19.76
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7ede95539800>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ede955398a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ede95539940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ede955399e0>", "_build": "<function ActorCriticPolicy._build at 0x7ede95539a80>", "forward": "<function ActorCriticPolicy.forward at 0x7ede95539b20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ede95539bc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ede95539c60>", "_predict": "<function ActorCriticPolicy._predict at 0x7ede95539d00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ede95539da0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ede95539e40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ede95539ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ede956989c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1744623409842625721, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c00712f06a2a8c6afeb64cc3c7da5c4bfbccee6341d365d5244a37b6e6202530
+size 148131

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7ede95539800>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ede955398a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ede95539940>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ede955399e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ede95539a80>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ede95539b20>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ede95539bc0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ede95539c60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ede95539d00>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ede95539da0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ede95539e40>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ede95539ee0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7ede956989c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1744623409842625721,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d3eab7b103e98ef478052f6e322ba837278cf736b58f72f8528790fc2c4647bc
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9c61e9f6f769ff26ed3df1b4331bf4f77b6fd3f8b1b800edfa356c2830c06db
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.11.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:159c1b5b68b45554617787045869315cc645517d31ac5bc210e02cbc18dead50
+size 171887

results.json

@@ -0,0 +1 @@
+{"mean_reward": 239.13126079227982, "std_reward": 19.761527564330436, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-14T10:19:18.946264"}